Paper Contents
Abstract
Misinformation has become one of the most dangerous issues of our time due to the widespread use of digital platforms. On social media, misleading or false information spreads swiftly, affecting political narratives, public opinion, and occasionally even igniting panic. It may cause public agitation and lead to political or other problems. Machine learning models that have been trained using fixed datasets form the basis of many of the fake news detection systems in use today. They do well on well-known patterns, but they struggle with novel or changing forms of false information. Another major obstacle is the diversity of languages. Regional languages used in India and other multilingual regions are less effectively detected by most detection systems, which are primarily made for English.This study suggests a real-time AI-powered fake news detection system that can evaluate content in several languages in order to get around these restrictions. In order to understand the deeper meaning of the content, translate text when necessary, and interpret claims, this system makes use of the Gemini API. In order to verify information, it also integrates with fact-checking APIs such as Google Fact Check Tools.
Copyright
Copyright © 2025 Tanvir Malnas, Ojaswi Bangare, Bhuwan Kanampalliwar, Ritesh Meshram, Tushar Pawar, Sushama Telrandhe, Mahendra Patil. This is an open access article distributed under the Creative Commons Attribution License.
